This invention relates to sensor systems and, more particularly, to vehicle sensor systems.
Sensor systems are widely known and used in vehicles and other applications for making algorithmic decisions in response to sensor measurements. A vehicle crash sensor system, for example, utilizes sensors to measure vehicle deceleration, relative pressure changes within a cavity, or other physical behaviors on the vehicle to decide whether to deploy one or more vehicle occupant restraints.
On occasion, one or more of the sensors used in the sensor system may malfunction because of an electrical failure, damage to the sensing elements of the sensor, or other reason. A malfunctioning sensor may produce measurements that do not represent the actual vehicle movement. For example, a sensor that detects vehicle roll-over may malfunction and cause an airbag deployment decision on an upright vehicle, or a sensor that measures the vehicle lateral deceleration may malfunction and cause a side airbag deployment decision on a stationary vehicle.
A plausibility check has traditionally been used to prevent deployment decision from executing in the case of a single sensor malfunction. For example, once an algorithm gives a deployment decision, there must be agreement between two of the sensors that the vehicle is in a crash condition in order to execute the deployment decision. Thus, at least two of the sensors must produce measurements that indicate a vehicle crash to deploy the vehicle airbag. However, conventional plausibility methods are often too sensitive and may be fulfilled under relatively normal driving conditions. For example, a vehicle driving over large bumps or potholes, or aggressive cornering, may cause one or more of the sensors to meet plausibility which could allow a malfunctioning sensor to trigger an occupant restraint to deploy. Even the slamming of a door could meet the plausibility conditions for a side airbag deployment if a side crash sensor is malfunctioning.
There are known sensor diagnostic methods that can be used to detect some sensor failures. One such method detects a failed sensor when it's offset drifts out of an acceptable range. Such methods usually take a relatively long time to detect and qualify. During the detection and qualification time there is a risk that the failing sensor is giving “crash-like” output and that plausibility could be met from another sensor thereby triggering an undesired occupant restraint deployment. Accordingly, it is desired to detect malfunctioning sensors as quickly as possible thereby minimizing the risk window of an undesired restraint deployment.